• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.564-566
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• 2003

There are no immutable phenomena in reality. A lot of applications are dealing with data characterized by spatial and temporal and/or uncertain features. Currently, there has no any data model accommodating enough those three elements of spatial objects to directly use in application systems. For such reasons, we introduce a fuzzy spatio -temporal data model (FSTDM) and a method of integrating temporal and fuzzy spatial operators in a unified manner to create fuzzy spatio -temporal (FST) operators. With these operators, complex query expression will become concise. Our research is feasible to apply to the management systems and query processor of natural resource data, weather information, graphic information, and so on.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.309-312
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• 2011

Handling fuzzy query in voice search on smartphones is one of the most difficult problems. It is mainly derived from the complexity and the degree of freedom of natural language. To reduce the complexity and the degree of freedom of fuzzy query in voice search on smartphones, attribute-driven approach for fuzzy query is proposed. In addition, a new page ranking algorithm based on the values of attributes for handling fuzzy query is proposed. It provides a smartphone user with location-based personalized page ranking based on user's search intentions. It is a further step toward location-based personalized web search for smartphone users. In this paper, we design a prototype model for handling fuzzy query in voice search on smartphones and show the experimental results of the proposed approach compared to existing smartphones.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.3
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• pp.265-269
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• 2005

A fuzzy query language, called FSQL, in the relational databases is introduced in this paper. In general, database systems have query systems which are able to retrieve and manipulate precise data. However, such queries are hard to operate on the real world applications since their queries are often imprecise or incomplete. Recently, considerable attention has been given to research dealing with vagueness of the query in relational database systems. In this paper we have suggested an effective method of accepting vagueness of the query in data processing. The syntax of FSQL is formally defined with EBNF, and an interpreter of FSQL has been implemented as a prototype.

• Asia pacific journal of information systems
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• v.1 no.1
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• pp.87-101
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• 1991

The primary purpose of this study was to investigate a robust search methodology that could be used in full-text information retrieval systems. A robust search methodology is one that can be easily used by a variety of users (particularly naive users) and it will give them comparable search performance regardless of their different expertise or interests In order to develop a possibly robust search methodology, a fully functional prototype of a fuzzy knowledge based information retrieval system was developed. Also, an experiment that used this prototype information retreival system was designed to investigate the performance of that search methodology over a small exploratory sample of user queries To probe the relatonships between the possibly robust search performance and the query organization using fuzzy inference logic, the search performance of a shallow query structure was analyzes. Consequently the following several noteworthy findings were obtained: 1) the hierachical(tree type) query structure might be a better query organization than the linear type query structure 2) comparing with the complex tree query structure, the simple tree query structure that has at most three levels of query might provide better search performance 3) the fuzzy search methodology that employs a proper levels of cut-off value might provide more efficient search performance than the boolean search methodology. Even though findings could not be statistically verified because the experiments were done using a single replication, it is worth noting however, that the research findings provided valuable information for developing a possibly robust search methodology in full-text information retrieval.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.270-273
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy theory. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.76-82
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• 2004

In this paper, we used query evaluation method through thesaurus for retrieving Components having concept relation with any classes in a query. Queries are presented in boolean and expanded by similar table. Query expansion by thesaurus is the solution of the term mismatching and it enhanced precision and recall of the components retrieval. For efficiency evaluation of query expansion, we defined most critical value through a simulation and compared precision and recall each other.

• The Journal of Information Systems
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• v.6 no.2
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• pp.147-163
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• 1997

The usages of the relational database systems have been increased nowadays. However there is a constraint that the standard query language for a database system requests users to know the exact condition for a query. In this paper a FSQL(Fuzzy SQL) systems is proposed and implemented for the imprecise queries which do not include the exact condition. Moreover this system can supply the obvious results for the queries effectively. We define a simple fuzzy query language and use a method using the metadatabase to implement the FSQL system. This FSQL system can be combined with a relational database system without any painful effort.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3689-3696
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• 2011

In decision support system, knowledge workers require aggregation operations of the large data and are more interested in the trend analysis rather than in the punctual analysis. Therefore, it is necessary to provide fast approximate answers rather than exact answers, and to research approximate query answering techniques. In this paper, we propose a new approximation query answering method which is based on Fuzzy C-means clustering (FCM) method and Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed method using FCM-ANFIS can compute aggregate queries without accessing massive multidimensional data cube by producing the KR model of multidimensional data cube. In our experiments, we show that our method using the KR model outperforms the NMF method.

• Journal of Information Management
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• v.24 no.3
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• pp.73-100
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• 1993

In attempting to respond to boolean retrieval system's limitations, this paper presents the design of a retrieval system using fuzzy logic. The fuzzy retrieval system introduces the weights of terms in the documents and in the query and makes use of them to determine how much relevant a document is to the given query. After comparing and analyzing the previous researches, an effective model of the fuzzy retrieval system is suggested and the performance of the system is evaluated through actual examples.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.259-265
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• 2003

It leads to develop the query system with artificial intelligent technologies to handle inaccurate query. To develop the query system, metadata is essential to control a uncertain data, providing information about uncertainty of the data, and the classification system of metadata are necessary. This paper shows a classification of metadata based on fuzzy theory and the implementation processing to process the fuzzy query in a relational database system.